Machine Learning Engineer
Pierre-Alexandre Fonta is a Machine Learning Engineer in the Simulation Neuroscience Divison.
At Blue Brain, he is currently creating solutions based on Natural Language Understanding and Deep Learning to perform Knowledge Extraction on scientific literature. This involves building, training, fine-tuning, evaluating, and validating Transformer-based models. During his work, he collaborates closely with Blue Brain Scientists and Developers.
Pierre-Alexandre joined the Machine Learning team from the Neuroinformatics team and his professional focus has always been the joint extraction, analysis, and visualization of the semantic content and the social networks of texts and scientific literature.
Before joining Blue Brain, he worked both in academia and in the private sector. In academia, he was part of an NCCR at the University of Geneva where he contributed to Machine Learning tools for Computational Social Sciences. Prior to that, he created data-driven methods and AI solutions for Strategic Foresight at a Business School of the University of Applied Sciences and Arts of Western Switzerland.
In the private sector, he prototyped for Randstad an AI platform for Human Resources Analytics as part of the multinational – Capgemini.
Pierre-Alexandre has a Master’s of Science in Machine Learning, Data Science, and Engineering from a French ‘Grande École’ (University of Technology of Compiègne, 2013). As part of the curriculum, he completed the ‘Classes Préparatoires aux Grandes Écoles’ in Science, where he followed the Pure Mathematics track.
In 2015, his team won the first prize at the SRG SSR Hackdays, after designing and building a solution to extract, explore, and visualize the events of the Arab Spring reported across five years of news articles. The events can be visualized interactively and explored thematically, spatially, and chronologically.
In his free time, Pierre-Alexandre enjoys being in touch with nature during long hikes. When he is not outside, he likes playing cooperative adventure and strategy board games with family and friends.
Logette, E., Lorin, C., Favreau, C., Oshurko, E., Coggan, J. S., Casalegno, F., Sy, M. F., Monney, C., Bertschy, M., Delattre, E., Fonta, P.-A., Krepl, J., Schmidt, S., Keller, D., Kerrien, S., Scantamburlo, E., Kaufmann, A.-K., & Markram, H. (2021). A Machine-Generated View of the Role of Blood Glucose Levels in the Severity of COVID-19. Frontiers in Public Health, 9, 1068. https://doi.org/10.3389/fpubh.2021.695139